Ble networking systems and methods providing central and peripheral role reversal with enhanced peripheral location determination

ABSTRACT

Provided are systems and methods for reversing the conventional roles of central and peripheral devices in a BLE network. Doing so includes implementing an end node (EN) as the sole initiator of a connection between a particular EN and a particular access point (AP). Such implementation includes determining a location of the EN based on position information for multiple reference points (RPs), which may in instances be supplied by the AP. Advantageously, the relative positioning is more particularly based on the received signal strengths (RSS) of beacon advertisement messages broadcast from the RPs, and refined by each of the position information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This is a continuation-in-part of application Ser. No. 15/626,083, filed Jun. 17, 2017, the entire contents of which are hereby incorporated by reference, and to which priority is claimed under 35 U.S.C. § 120.

FIELD OF THE DISCLOSURE

Disclosed embodiments relate to wireless communications, and more specifically, to wireless communication among BLUETOOTH Low Energy (BLE) equipped devices in which conventional BLE central and peripheral roles of those devices are reversed and made applicable to nodes of a BLE-enabled network so as to enhance BLE networking capability, including refining determinations of a location of a node operating as a peripheral.

BACKGROUND

Circa 2009, the Internet was in a stage of its evolution in which the backbone (routers and servers) was connected to fringe nodes formed primarily by personal computers. At that time, Kevin Ashton (among others) looked ahead to the next stage in the Internet's evolution, which he described as the Internet of Things (“IoT”). In his article, “That ‘Internet of Things’ Thing,” RFID Journal, Jul. 22, 2009, he describes the circa-2009-Internet as almost wholly dependent upon human interaction, i.e., he asserts that nearly all of the data then available on the internet was generated by data-capture/data-creation chains of events each of which included human interaction, e.g., typing, pressing a record button, taking a digital picture, or scanning a bar code. In the evolution of the Internet, such dependence upon human interaction as a link in each chain of data-capture and/or data-generation is a bottleneck. To deal with the bottleneck, Ashton suggested adapting internet-connected computers by providing them with data-capture and/or data-generation capability, thereby eliminating human interaction from a substantial portion of the data-capture/data-creation chains of events.

In the context of the IoT, a thing can be a natural or man-made object to which is assigned a unique ID/address and which is configured with the ability to capture and/or create data and transfer that data over a network. Relative to the IoT, a thing can be, e.g., a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low, field operation devices that assist fire-fighters in search and rescue, personal biometric monitors woven into clothing that interact with thermostat systems and lighting systems to control HVAC and illumination conditions in a room continuously and imperceptibly, a refrigerator that is “aware” of its suitably tagged contents that can both plan a variety of menus from the food actually present therein and warn users of stale or spoiled food, etc.

In the post-2009 evolution of the Internet towards the IoT, a segment that has experienced major growth is that of small, inexpensive, networked processing devices, distributed at all scales throughout everyday life. Of those, many are configured for everyday/commonplace purposes. For the IoT, the fringe nodes will be comprised substantially of such small devices.

Within the small-device segment, the sub-segment that has the greatest growth potential is embedded, low-power, wireless devices. Networks of such devices are described as comprising the Wireless Embedded Internet (“WET”), which is a subset of IoT. More particularly, the WET includes resource-limited embedded devices, which typically are battery powered, and which are typically connected to the Internet by low-power, low-bandwidth wireless networks (“LoWPANs”).

The BLUETOOTH Special Interest Group devised BLE particularly in consideration of IoT devices and applications which do not rely upon continuous connection(s), but depend on extended battery life. A good example of these devices includes a temperature sensor which intermittently provides temperature readings to a collector device that collects such readings. That is, continuous connection between the sensor and collector is not necessary to obtain, for example, such temperature reading at a discrete point in time.

The BLUETOOTH specification governing operation of BLE devices relates definitional roles to each of the above sensor and collector as peripheral and central, respectively.

In accordance with customary BLE networking operations, a peripheral, such as a sensor above, makes its presence known to any central, such as a collector above, merely by continuously “advertising” its presence. In other words, the peripheral continuously sends beacon advertisement messages for recognition by a central that itself decides whether connection with the recognized peripheral should occur. In a BLE environment, such advertising occurs across three advertising channels, or frequencies, so as to reduce instances of interference among signals sent by multiple peripherals.

Yet, existing within such a BLE environment are several impediments to optimal communication between a peripheral device, such as an end node (EN), and a central device, such as an access point (AP).

An example of such an impediment exists in the form of an uncertainty that a peripheral device may experience in actually knowing why its broadcast advertisement has not been acknowledged by a central device. Specifically, such uncertainty exists due to the peripheral's inability to know whether a central device is in a range enabling receipt of its advertisement, or additionally, whether a central device that is in range is simply overloaded such that it has not had sufficient time or capacity to process the peripheral's advertisement.

Yet a further impediment that exists to an optimal relationship between a peripheral and central is congestion across the advertising channels leading to opportunities for signaling collision and missed advertisements, each of which causes a lack of connection. These failures are prevalent in scenarios in which multiple peripherals are co-located, i.e., disposed in or at a same space within a structure such as a building or other venue in which peripheral and central functionality are required or desired.

A still further impediment to BLE networking exists in the fundamental complexity brought about by the conventional BLE peripheral/central relationship. In this relationship, a mobile peripheral which moves out of range of a central such as a first network access point (AP) to which it had previously connected essentially loses any established relationship that such peripheral made with that first AP. In this case, when the peripheral moves within range of another, second AP, this second AP is not immediately able to know, due to the established relationship of the peripheral with the first AP, whether a connection should be made in view of considerations including network configuration, security and authentication. The only basis for informing the second AP whether connection with the peripheral should occur is information it receives from a coordinating application running on the BLE network and that provides information to APs concerning whether connection should be made with a peripheral as a result of its broadcast advertisement. However, by the time the coordinating application learns of the lost connection with the first AP in the above scenario, a considerable amount of time has elapsed before connection information can be, or is, provided by the coordinating application to the second AP in order to allow it to determine that it should connect with the peripheral. Thus, in these ways, it will be understood that enabling connection with a peripheral moving among several APs is not only complex, but further disadvantages exist insofar as increased connection latency and a higher utilization of backhaul due to necessary information that must flow to and from the coordinating application.

Also, in the context of BLE and other RF communication protocols there sometimes exists barriers to receipt of signaling among intended devices. These barriers may, as alluded to above, be due to natural occurrences such as congestion, or otherwise be defined by artificial structures in the vicinity or vicinities in which operation of the devices is desired. As a consequence, important information which is associated with a respective one or more of the devices, such as its location or other collected and communicable data may be unable to be delivered with optimum efficiency and accuracy. Because of this, operators of systems dependent upon knowing such important information may be denied the capability to carry out intended duties, such as those which may be involved in encompassing project tasks like those of asset tracking and temperature or other variable monitoring, just to name of few.

Thus, it would be desirable to provide for one or more optimized BLE networking relationships that address and overcome the aforementioned impediments and disadvantages now associated with the conventional BLE central/peripheral networking relationship discussed above. More specifically, it would be desirable to provide applicability of such optimized BLE relationships in connection with various application environments such as, for example, providing healthcare, improving fitness, improving internet connectivity, improving proximity sensing, improving alert systems, improving jobsite monitoring, improving systems controlling access, improving automation and improving systems and methods for tracking assets to be inventoried and for which location must be determined, whether in a commercial or residential setting, as well as any other application in which a BLE networking protocol is deployed.

SUMMARY

It is to be understood that both the following summary and the detailed description are exemplary and explanatory and are intended to provide further explanation of the present embodiments as claimed. Neither the summary nor the description that follows is intended to define or limit the scope of the present embodiments to the particular features mentioned in the summary or in the description. Rather, the scope of the present embodiments is defined by the appended claims.

An aspect of the embodiments includes a BLE communications system having an end node (EN), an access point (AP) configured to connect to a network and transmit a first beacon advertisement message, and a plurality of reference points (RPs) each configured to not connect to the network and transmit a second beacon advertisement message comprising position information. The EN is configured to detect the first and second beacon advertisement messages, initiate a connection with the AP in which, as a result of the connection, the AP is caused to transfer to the network identifying information of each of the EN and the AP, and determine, as against others of the plurality of RPs, whether a proximity of a respective one of the plurality of RPs to the EN is a nearest proximity based on the position information and a received signal strength (RSS) of each of the detected second beacon advertisement messages. Further, the EN determines whether to initiate the connection with the AP in response to evaluating from the detected first beacon advertisement message at the time of transmission of the first beacon advertisement message each of at least (a) whether a proximity of the AP to the EN is a nearest proximity and (b) a loading of the network to which the AP is connected, and transmits, via the connection, identifying information of the respective one of the plurality of RPs to the network in response to a determination that the respective one of the plurality of RPs is nearest in proximity to the EN, from among others of the plurality.

A further aspect of the embodiments includes a method of BLE communication providing for executing, by one or more processors among a BLE end node (EN), a BLE access point (AP) configured to connect to a network, and a plurality of BLE reference points (RPs) configured to not connect to the network, a set of instructions for transmitting a first and a second beacon advertisement message from the AP and each of the plurality of RPs, respectively, each second beacon advertisement message comprising position information, detecting the first and the second beacon advertisement messages at the EN, and also initiating a connection between the AP and the EN, in which, as a result of the connection, the AP is caused to transfer to the network identifying information of each of the EN and the AP. Additionally, the EN conducts determining, as against others of the plurality of RPs, whether a proximity of a respective one of the plurality of RPs is a nearest proximity based on the position information and received signal strengths (RSSs) of the second beacon advertisement messages. In these contexts, the EN determines whether to initiate the connection with the AP in response to evaluating from the detected first beacon advertisement message at the time of transmission of the first beacon advertisement message each of at least (a) whether a proximity of the AP to the EN is a nearest proximity and (b) a loading of the network to which the AP is connected, and also transmits, via the connection, identifying information of the respective one of the plurality of RPs to the network in response to a determination that the respective one of the plurality of RPs is nearest in proximity to the EN, from among others of the plurality.

In certain embodiments, the disclosed embodiments may include one or more of the features described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate exemplary embodiments and, together with the description, further serve to enable a person skilled in the pertinent art to make and use these embodiments and others that will be apparent to those skilled in the art. Embodiments herein will be more particularly described in conjunction with the following drawings wherein:

FIG. 1 is an illustration of BLE transmission of a beacon advertisement message between a BLE central and a BLE peripheral, according to the related art;

FIG. 2 is an illustration of BLE transmission of a beacon advertisement message between a BLE end node (EN) and a BLE access point (AP), according to embodiments disclosed herein;

FIG. 3 is an illustration of a BLE-enabled network in accordance with FIG. 2;

FIG. 4 is a sequence diagram of proximity association of a BLE EN with a BLE AP, in accordance with FIG. 3;

FIG. 5 is a sequence diagram of detection, by a BLE EN, of a BLE AP, in accordance with FIG. 3;

FIG. 6 is a sequence diagram of connection, by the BLE EN, with the BLE AP, in accordance with FIGS. 3 and 5;

FIG. 7 is an illustration of a zonal configuration of BLE reference points (RPs) relative to which the BLE EN may determine a nearest proximity to one or more thereof, according to embodiments disclosed herein;

FIG. 7A is a diagrammatic illustration of a nearest proximity determination according to a trilateration technique according to embodiments disclosed herein; and

FIG. 8 is a sequence diagram setting forth a manner in which the BLE EN may determine the nearest proximity in accordance with FIG. 7.

DETAILED DESCRIPTION

The present disclosure will now be described in terms of various exemplary embodiments. This specification discloses one or more embodiments that incorporate features of the present embodiments. The embodiment(s) described, and references in the specification to “one embodiment”, “an embodiment”, “an example embodiment”, etc., indicate that the embodiment(s) described may include a particular feature, structure, or characteristic. Such phrases are not necessarily referring to the same embodiment. The skilled artisan will appreciate that a particular feature, structure, or characteristic described in connection with one embodiment is not necessarily limited to that embodiment but typically has relevance and applicability to one or more other embodiments.

In the several figures, like reference numerals may be used for like elements having like functions even in different drawings. The embodiments described, and their detailed construction and elements, are merely provided to assist in a comprehensive understanding of the present embodiments. Thus, it is apparent that the present embodiments can be carried out in a variety of ways, and does not require any of the specific features described herein. Also, well-known functions or constructions are not described in detail since they would obscure the present embodiments with unnecessary detail.

The description is not to be taken in a limiting sense, but is made merely for the purpose of illustrating the general principles of the present embodiments, since the scope of the present embodiments are best defined by the appended claims.

It should also be noted that in some alternative implementations, the blocks in a flowchart, the communications in a sequence-diagram, the states in a state-diagram, etc., may occur out of the orders illustrated in the figures. That is, the illustrated orders of the blocks/communications/states are not intended to be limiting. Rather, the illustrated blocks/communications/states may be reordered into any suitable order, and some of the blocks/communications/states could occur simultaneously.

All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of’ “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.

It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.

The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Additionally, all embodiments described herein should be considered exemplary unless otherwise stated.

The word “network” is used herein to mean one or more conventional or proprietary networks using an appropriate network data transmission protocol, or other specification and/or guidelines which may be applicable to the transfer of information. Examples of such networks include, PSTN, LAN, WAN, WiFi, WiMax, Internet, World Wide Web, Ethernet, other wireless networks, and the like.

The phrase “wireless device” is used herein to mean one or more conventional or proprietary devices using radio frequency transmission techniques or any other techniques enabling the transfer of information. Examples of such wireless devices include cellular telephones, desktop computers, laptop computers, handheld computers, electronic games, portable digital assistants, MP3 players, DVD players, or the like.

BLE networking enables detection and connection among devices that generally do not require continuous connection therebetween in order for an exchange of information in the form of data to occur. Yet, such devices depend upon extended battery life in order that the opportunity for such an exchange may continue to reliably exist. The devices themselves vary in their construction, whether, for example, a sensor, a cellphone, a network access point (AP), or some other object configured to enable and/or provide BLE communication(s) and which is either stationary or mobile, such as a BLUETOOTH tag. In the context of BLE networking, such devices are prescribed by the BLUETOOTH Core Specification 4.0 and are compatible with IEEE 802.15.1, as appropriate.

Typically, in the context of BLE communications, one or more of these devices assume the roles of a central 10 and a peripheral 12, as shown in FIG. 1. A peripheral is generally understood as a device which merely broadcasts, or advertises, its presence toward another device referred to as a central, with the intent that such presence be detected by that central. The broadcast generally takes the form of a beacon advertisement message transmitted as a radio frequency (RF) signal. Should detection occur, it is also generally understood that it is the central that determines whether a connection with the peripheral should occur. If the answer to that determination is in the affirmative, the central establishes a connection, and also prescribes all conditions under which any connection with a peripheral is to be made. The directional flow of transmission of the beacon advertisement message comprising a RF signal from the peripheral is shown by arrows “A,” in FIG. 1, while the directional flow of establishment of a connection with the peripheral by the central is shown by arrows “B.”

Such a scheme renders BLE networking susceptible to the many shortcomings discussed hereinabove.

Thus, in an effort to address those shortcomings, embodiments disclosed herein reverse the directional flows of transmission of the beacon advertisement message and connection so as to thereby reverse the roles of a conventional central and a conventional peripheral, and make such role reversal applicable to appropriate nodes in a BLE-enabled network.

FIG. 2 illustrates such reversal of roles insofar as each of exemplary BLE end nodes (ENs) 14 are responsible for detection of a beacon advertisement message transmitted from an exemplary BLE access point (AP) 16 in the direction of arrows “A,” and moreover, whereby such ENs 14 are solely responsible for evaluating and/or determining whether to initiate and/or establish a BLE connection with the AP 16, as shown in the direction of arrows “B.” That is, in no way is the AP 16 responsible for evaluating and/or determining any aspect or aspects of whether to make a connection between a respective AP 16 and a respective EN 14, and whereas such aspect or aspects, rather, are solely evaluated and/or determined by the EN 14 so that the EN 14, itself, is enabled to then solely initiate and/or establish the aforementioned connection, if doing so is deemed appropriate by the EN 14. Herein, the term, “initiate” means taking any initial steps or enacting any initial procedures, and the terms, “establish,” or “established” mean taking any steps or enacting any procedures related to whether to cause and/or maintain a connection between an AP 16 and an EN 14, and thereafter making and/or maintaining such connection.

FIGS. 3-6 and their accompanying descriptions below address various manner of associating an EN 14 to an AP 16. Therein, FIG. 3 illustrates a BLE-enabled network and communications system thereof, FIG. 4 illustrates a manner of proximity association of a BLE EN to a BLE AP, FIG. 5 illustrates a manner of detection, by a BLE EN, of a BLE AP, and FIG. 6 illustrates a manner of connection, by a BLE EN, with a BLE AP. Throughout, it is to be understood that an EN 14 does not, at any time, transmit to an AP 16 its location, but rather, the location of the EN 14 may be determined by relative association of one or more APs 16 or reference points (RPs) 17.

Specifically, FIG. 3 illustrates a BLE-enabled network 18 and communications system thereof according to the present embodiments in which ENs 14 detect a received signal strength (RSS) of all beacon advertisement messages transmitted from the APs 16, solely determine proximity with respect to the APs 16, and further, solely initiate and establish all connections therebetween the ENs 14 and APs 16, in response to having evaluated and/or made a decision with respect to, for example, such RSS, information contained in the beacon advertisement message, and/or other information, as discussed below in regard to FIGS. 4-6. Once a connection between an EN 14 and an AP 16 is made, data such as, optionally, identifying information, other than location information, of the EN 14 and identifying information of, other than the connected AP 16, the most proximate AP 16, and contained information of the EN 14 including, for example, sensory information thereof, may be transferred to the respective AP 16 for delivery through a backhaul 20, implemented by a cellular, WiFi, or Low Power Wide Area Network (LPWAN) configuration, to a network or cloud service 22 for transfer to an end user terminal 24, such as a personal computing or other electronic device enabled to convey the aforementioned information. Pertinent identifying and/or location information of the APs 16 and RPs 17 are known to the network 22. Such network or cloud service 22 includes any one of available data and connectivity platforms to allow users of nodes within network 18 to, for instance, manage and distribute information pertinent to the nodes and/or information desired in the administration of the nodes. An example of such a platform is CONDUCTOR, available from Link Labs, Inc. of Annapolis, Md.

As mentioned, EN 14 may transmit identifying information, i.e., the media access control (MAC) address, of the AP 16 which is most proximate to the EN 14. Such AP 16 may or may not be an AP 16 which is connectable to the network 22, as is explained below. In these regards, it is to be understood that an AP 16 is connectable if able to connect to the network 22 via backhaul 20, and as non-connectable if unable to make such connection. For instance, non-connectable APs 16 defining RPs 17, which may or may not be present in the network 18 according to FIG. 3, are shown in dashed lines, as are transmissions of their beacon advertisement messages.

Relative to communications between an EN 14 and an AP 16, network 22 is configured to message an EN 14, in order to provision certain ones of settings of the EN 14. Among these settings are aspects of a heartbeat message, i.e., a message sent by the EN 14 to the network 22 which informs the network 22 of the communication state of the EN 14. As examples, such aspects may include one or more of a battery configuration, a heartbeat message interval defining a period of time between transmissions of heartbeat messages, “scans per fix” defining a number of scans to be conducted for every proximity location determination of a most proximate stationary AP 16, as well as any update information in relation to any of the aforementioned aspects. A transmitted heartbeat message will include the MAC address of a most proximate stationary AP 16 and/or RP 17.

Further, it is to be understood that, while communications between an EN 14 and AP 16 are discussed herein in the context of the BLE protocol, it is contemplated that such communication may also be optionally achieved according to another wireless protocol, as appropriate. Also, it is to be understood that EN 14 and AP 16 are exemplary of first and second network nodes, respectively, which may be similarly configured as are EN 14 and AP 16 to carry out communications with respect to the BLE networking described herein and/or according to the other, appropriate wireless protocol discussed above.

In an exemplary case in which a respective EN 14 is mobile, the EN 14 is configured with an estimator comprising appropriate software and/or hardware for causing an estimating of proximity to a given AP 16 or RP 17, based on RSS, and is also configured with appropriate software and/or hardware for performing all operations associated with initiating and/or establishing a connection with an AP 16. All discussion herein regarding a determination of proximity of an AP 16 is to be understood as being equally applicable to determination of proximity of a RP 17.

The estimator conducts a Bayesian Estimation, and specifically a maximum a posteriori (MAP) estimation for each AP 16 encountered by the mobile EN 14 at the time of the encounter, i.e., at the time of receipt of a single or multiple beacon advertisement messages, so as to account for either a single RSS, or alternatively, multiple RSSs. In other words, the MAP estimation may reflect either (1) a single RSS at the time of receipt of a beacon advertisement message from the respective AP 16 or (2) in order to mitigate RF hopping, a predetermined number of consecutive RSSs, e.g., five RSSs, resulting from multiple beacon advertisement messages from the respective AP 16. Furthermore, the EN 14 and its estimator may also be configured to undertake the MAP estimation at any time during operation of the EN 14. The estimation is given by the following Equation (1),

p(x _(t) |y _(1:N))=p(y _(1:N) |x _(1:N))∫p(x _(t) |x _(t-1))p(x _(t-1) |y _(t-1))dx _(t-1).  Equation (1)

In this way, the posterior distribution, p(x_(t)|y_(1:N)), for a given proximity between a particular EN 14 and AP 16 pair at time, t, is determined. In particular, such determination is made by advancing the next most previous posterior, p(x_(t-1)|y_(t-1)) from time, t−1, to the current time, t, given p(x_(t)|x_(t-1)). It is contemplated that a variance of the previous estimate, p(x_(t-1)|y_(t-1)), is increased by a predetermined rate. Accordingly, a new posterior estimate may be obtained based on all observations by an EN 14 in accordance with Equation (2), as follows:

$\begin{matrix} {{p\left( y_{1:N} \middle| x_{1:N} \right)} = {\prod\limits_{i = 1}^{N}\; {{p\left( y_{i} \middle| x_{i} \right)}.}}} & {{Equation}\mspace{14mu} (2)} \end{matrix}$

Therein, x_(i) represents a variable distance from an EN 14 to an AP 16, y_(i) represents a RSS of a beacon advertisement message and N represents a number of observations, i.e., a number of received beacon advertisement messages. In this regard, the highest value, or minimum variance, distribution is chosen as the MAP estimate.

Once the MAP estimate is obtained, a confidence value, representing a level of expectation that a respective AP 16 is most proximate to the EN 14, is calculated for each AP 16 encountered by the EN 14, based on the estimated posterior distribution and Equation (3) below, and insofar as a 10 dB predetermined variance in RSS is set as an optional, acceptable variance therefor:

$\begin{matrix} {P_{\overset{\_}{10\; {dB}}} = {1 - {2{{Q\left( \frac{10\mspace{11mu} {dB}}{\sigma_{posterior}} \right)}.}}}} & {{Equation}\mspace{14mu} (3)} \end{matrix}$

Thus, it is to be understood that another variance level could be set as the predetermined variance depending upon, for example, device configuration(s) of one or more of the AP 16 and EN 14.

Selection of which AP 16 is most proximate to the EN 14 is determined as that AP 16 which yields the highest confidence value. However, if a further AP 16 yields a next most confident value corresponding to a predetermined tolerance for the confidence value, selection of the AP 16 that is most proximate to the EN 14 is determined from among all of the APs 16 which have broadcast a beacon advertisement message received by the EN 14. Still further, a signal strength from a respective AP 16 may be adjusted, in accordance with an adjustment factor included in the beacon advertisement message, to confer exclusive selection thereof by the EN 14, i.e., any other AP 16 whose beacon advertisement message the EN 14 has received is excluded from being considered as being most proximate to the EN 14. It is to be understood, that the estimator of a particular EN 14 may be configured to create a statistical fingerprint of AP 16 associations so as to optimize interpretation of future association patterns.

FIG. 4 sets forth a sequence of the above proximity determination enabling association of a respective EN 14 to a respective AP 16.

Therein, flow begins at decision block 410 and proceeds to decision block 420 at which an EN 14 receives a RSS from one or more APs 16. Thereafter, at decision block 430, the EN 14 measures the RSSs. At decision block 440, the estimator, which is configured integrally with the EN 16, calculates a MAP estimation for each of the RSSs. Subsequently, at decision block 450, EN 14 calculates a confidence value from each of the estimated posterior distributions. At decision block 460, the AP 16 yielding a highest confidence value is selected as the most proximate AP 16 to the EN 14. Flow then proceeds to decision blocks 470-480 in response to the selection by the EN 14. At decision block 470, EN 14 records the selection of the AP 16 according to identifying information thereof, including, for example, its network address or other appropriate networking identifying information. At decision block 480, the proximity association process ends.

Furthermore, it is contemplated that EN 14 may modulate its behavior depending upon certain conditions. For example, EN 14 may vary the frequency with which it conducts its MAP estimate depending upon whether the EN 14 is stationary or moving. That is, EN 14 may perform its estimation more frequently if it is moving, and less often if it is stationary. Still further, EN 14 may be configured to perform some predetermined action depending upon whether it is at a predetermined location (e.g., activate a light-emitting device (LED) or alarm) and/or whether no further AP 16 is detected (e.g., deactivate a device).

Additionally, and in accordance with FIGS. 5-6, the decision as to which AP 16 a mobile EN 14 should connect with, and to which it may transmit the identifying information of the most proximate AP 16, is determined based on attainment of a highest connection value calculated by the mobile EN 14. That is, as a mobile EN 14 moves in proximity to one or more APs 16, the value of connection with any one of the APs is assessed based on several components including the confidence value, in accordance with FIG. 4, and an associated weighting factor, a network loading value and an associated weighting factor, and an association factor of the broadcasting AP 16, and is given by the following Equation (4):

σ=α·P·β·L·γ, in which  Equation (4)

σ represents the connection value, as an absolute value, α represents a weighting factor assigned to the confidence value calculated by the EN 14, P represents the confidence value, β represents a weighting factor assigned to loading of the connected network, L represents a loading value of the connected network and is included in the beacon advertisement message, and γ represents an association factor for a respective AP 16, such that γ equals zero if the EN 14 has not made a previous connection with the respective AP 16 and equals a predetermined highest value if the respective AP 16 is the AP 16 with which the EN 14 has made a most previous connection.

In this way, an EN 14 that moves among various APs 16, which may or may not be connectable to the network 22, may determine an optimal connection among such APs 16 based on the aforementioned components yielding the highest connection value in accordance with Equation 4.

Once such connection is made, as indicated by the exemplary double arrows of FIG. 3, the connected AP 16 may receive from the EN 14 the identifying information of another AP 16 that is most proximate in a case in which the connected AP 16 has been determined to have attained the highest connection value, but not the highest confidence value. The other, most proximate AP 16 may include another connectable AP 16, indicated at 26 in FIG. 3, to which connection has not been made due to it not achieving the highest connection value. Thus, it is to be understood that the consideration of the confidence value in Equation 4 increases the likelihood that the most proximate AP 16 is the one to which EN 14 connects. However, this scenario is not certain given connectability of one or more APs 16 and other considerations used in determining the connection value according to Equation (4).

The manner of determining the above optimal connection at the mobile EN 14 is demonstrated by the flow of FIGS. 5-6. FIG. 5 provides a sequence for scanning for detection of a beacon advertisement message respectively transmitted from one or more APs 16, while FIG. 6 provides a sequence for determining an AP 16 with which the EN 14 should connect, based on the above-discussed connection value, a, as determined in accordance with Equation 4.

Flow begins in FIG. 5 at decision block 510 and proceeds to decision block 520 at which EN 14 scans for and detects a respective beacon advertisement message from one or more APs 16, whose identifying and/or location information is known to the network 22. Thereafter, at decision block 530, EN 14 processes a detected beacon advertisement message to determine a Universally Unique Identifier (UUID) match wherein identifying data of the AP 16 broadcasting the beacon advertisement message is confirmed as belonging to the network 22. From there, flow proceeds to decision block 540 to determine and confirm a token match. If a match is confirmed at 540, the broadcasting AP 16 is, at decision block 550, added to a list of detected APs 16 (“detection list”) for which decisions at blocks 530 and 540 have been confirmed. During operation of the estimator at decision blocks 520-540, the estimator of EN 14 calculates respective confidence values for the detected APs, and records each of the respective confidence values for the detected APs 16 such that attained confidence value is associated with a respective, detected AP 16 when such AP 16 is added to the detection list, and also its selection of the most proximate AP 16. Thereafter, it is determined at decision block 560 whether the scanning operation has timed out. If not, as in the case of negative decisions at decision blocks 530 and 540, scanning continues. If the scanning operation has timed out, flow proceeds, as shown in FIG. 6, to determine which AP 16, from among the detection list, the EN 14 should connect.

Based on a timeout having occurred and the detection list, flow then proceeds, from decision block 560, to decision block 610 of FIG. 6 so as to initialize a list of APs 16 to which the EN 14 should connect (so as to provide a “connection list”). Once this connection list is initialized, an AP 16, with its associated confidence value, is drawn from the detection list, at decision block 620, at which point it is then determined, at decision block 630, if such AP 16 is connectable to the network 22 of FIG. 3, for example. If the drawn AP 16 is connectable, flow then proceeds, with respect to such drawn AP 16, to decision block 640 whereat a connection value therefor is calculated in accordance with Equation (4). Flow is then iterative through decision blocks 620-640 until detection list provided at decision block 550 is empty. From among respective connection values calculated at decision block 640, EN 14 selects and connects with, at decision block 650, the AP 16 having a highest connection value in accordance with Equation (4), and proceeds to an end at decision block 660 once connection is established.

During that connection, however, identifying information, other than location information, of a RP 17 which is determined to be most proximate to the EN 14 may be transmitted, by the EN 14, to the AP 16 with which the aforementioned connection has been established.

In this way, the aforementioned proximity determination according to the discussed confidence value serves the dual purpose of both determining an estimate of which AP 16 and/or RP 17 is most proximate to an EN 14, and providing a basis for determining which AP 16 the EN 14 should connect. That is, the AP 16 with which the EN 14 ultimately connects may receive identifying information of a non-connectable RP 17 that is most proximate to the EN 14 so that a relative determination of the location of the EN 14 may be determined with reference to this latter, non-connectable RP 17. In this way, the granularity of the proximity determination above is increased such that non-connectable APs 16, and not only connectable RPs 17, are each considered by the estimator of EN 14 so as to render available a more accurate AP/EN proximity association.

Accordingly, as mobile EN 14 moves in and out of range of one or more APs 16, connection with a respective one thereof may be made based upon the aforementioned confidence and connection values, such that the connected AP 16 likewise may yield a highest confidence value so as to be most proximate to the EN 14, and represent the optimal connection according to Equation (4). In this case, such proximity will be made known to the user 24 by virtue of the established connection and the lack of any other AP 16 identifying information being transferred to the network 22.

Such ability of a EN 14 to select and connect with a specified, respective one of APs 16 removes the shortcomings of conventional BLE networking by enabling a mobile EN 14 to have the autonomy necessary to initiate and/or establish connection with an AP 16 solely in response to its own evaluation and decisionmaking with respect to aspects contributing to the aforementioned proximity association, connection value and/or other information associated with the EN 14. For instance, such other information may optionally include one or more parameters relating to operation of the EN 14.

In removing the aforementioned shortcomings, it will be apparent that the embodiments discussed herein eliminate the conventionally overwhelming number of advertisements transmitted by peripherals in conventional BLE networking. That is, the present embodiments substantially reduce the number of advertisements occurring at a given time by virtue of the BLE role reversal, discussed herein, in which plural end nodes receive, rather than transmit, advertisements in the form of beacon advertisement messages from one more access points.

Once connected, the EN 14 may then transfer its own identifying information, other than location information, and identifying information of the most proximate AP 16 and/or RP 17. In this way, when information of an AP 16 other than the connected AP 16 is not transferred, it will be understood that the connected AP 16 is most proximate to the EN 14. Concurrently with the transfer of the above information, the EN 14 may also transfer one or more of its contained information including sensory information, access information, notification information, alarm information, and any other status and/or content information thereof as may be applicable to its particular configuration. For instance, it is contemplated that EN 14 may transfer any of the aforementioned types of information so as to be applicable to such environments including a workplace or other type of commercial environment in which commerce is a purpose, a residence, and a medical facility or other facility in which tracking of persons or objects is necessary and/or desired.

The following examples describe instances of associating a particular end node (EN) 14 to a particular access point (AP) 16. Further, such examples are set forth in the context of the BLE-enabled network 18 of FIG. 3 and with the exemplary understanding that an EN 14, which may be defined as a BLE tag and/or a BLE tag attached to or associated with a particular object, is seeking association with a BLE AP 16 that is configured to report information of the tag to an end user 24 via backhaul 20 and network 22. In these regards, it is contemplated that EN 14 and AP 16 may be embodied as being any stationary and/or mobile nodes of an appropriate wireless network, and as being capable of operating according to a BLE protocol or other protocol in which such nodes may operate as respective first and second nodes according to any of FIGS. 4, 5, and/or 6. Also, in these regards, it is to be understood that a respective EN 14 may be configured to calculate its confidence and connections values at the same time, or, at different times. It is to be understood that EN 14 may undertake any of the processes of FIGS. 4-6 at any time, whether the EN 14 is mobile or stationary. Thus, the EN 14 is configured to optimize, at least, a rate at which connection may be established, with respect to, at least, proximity of such connection as well as the efficiency of such connection, as will be understood based on the components of Equation (4).

In a first instance, it is contemplated that such tag is attached to an object, such as a hospital bed for which it is desirous to know the location thereof at any given point in time when it is moving throughout a hospital environment. Thus, assume that the hospital bed, with the tag attached thereto, is transient throughout the hospital, moving from floor to floor and from room to room, as the case may be when a patient is to undergo a particular procedure. At any given point in time, as the bed moves from one location to the next, its whereabouts may be tracked through monitoring achieved by the BLE communications system disclosed herein.

More specifically, as the hospital bed may move throughout a particular floor, it contemplated that it will move among a number of APs whose location is known to the hospital network. As that travel occurs, the tag attached to the bed will scan for beacon advertisement messages transmitted from the various APs. Upon receipt of the transmitted signals, the tag is configured to conduct the MAP estimation discussed hereinabove and calculate a highest confidence value for the AP that is in closest proximity at a given point in time and which may or may not be connectable to the hospital network. The tag is further configured to connect with a particular connectable AP having a highest connection value, as shown by the exemplary double arrows extending between an exemplary EN 14 and AP 16 of FIG. 3, so that the identifying and other information of the closest proximity AP may then be transferred to the end user. In this way, as the bed and attached tag may continue to move, the process of determining proximity of the tag to both connectable APs 16 and non-connectable RPs 17 continues until, optionally, such point in time when the bed and attached tag are stationary such that identifying information of a further, different AP need not be reported.

More particularly, and continuing with the example scenario above, the attached tag is alternatively, and optionally, configured to conduct a scan of broadcasting APs and assess their UUID and token information so as to qualify those APs to be included on a detection list resulting from the scan and from which connection with a specified one thereof will occur in order to transfer the tag's identity, identity information of the AP to which the tag is most proximate, and/or contained information of the tag to an end user. Once this detection list is compiled and scanning is completed, embodiments of the present disclosure contemplate the tag being configured to initialize a connection list of APs, from among the APs compiled on the detection list. Once initialized, the tag is further contemplated to conduct a determination of whether an AP is connectable to the network 22 via backhaul 20 so as to be able to transfer information of the tag to an end user desirous of knowing the location of the hospital bed. Each connectable AP is then evaluated as to its associated connection value in accordance with Equation (4) above.

More specifically, the connection value for each AP, that is determined to be connectable to the network 22, is assessed based on components comprising a confidence value representing a level of expectation that a respective AP is most proximate to the tag and an associated weighting factor, a network loading value and an associated weighting factor, and an association factor of the AP. In regard to the association factor, it is contemplated that such factor be deemed to have a value of zero if the tag has not connected with the AP being evaluated, and to have a highest value if the tag has had its most recent connection with that AP. In this way, those connectable APs for whom a connection value has been evaluated by the tag will yield an AP having a highest connection value. As such, the tag will then select that AP as the AP with which to initiate and establish a connection enabling the transfer of pertinent information of the tag, including identity information of the AP to which the tag is most proximate, to the end user.

Discussion of the above embodiments contemplates that proximity to either an AP 16 or RP 17 may be determined by an EN's implementation of its estimator, i.e., through execution of Equations (1)-(3). As has been mentioned, inclusion of an RP 17 within these executions greatly increases the granularity of the resulting proximity determinations which enable a final determination of an actual position of the EN 14 at the network 22.

Innumerable settings provide for the opportunity to reap a variety of benefits to be gained from an ability to learn a precise location of assets, such as ENs (and/or objects with which they may be associated). These settings may include factories, crop fields, and buildings such as hospitals. Relatedly, the benefits may include an ability to track when and where materials, resources, and personnel are located at a given time. As a result, optimizations for the following non-limiting examples of scheduling, material allocation, and other types of productivity levels associated with heightening the prospect for attaining desired monetary and procedural goals which are in any way tied to knowing the location of an asset may be further made more obtainable when the accuracy of the asset's actual location is refined.

Many of the above settings would benefit from the placement therein of a plurality of RPs 17 and an ability to more acutely determine a location of an EN 14. Accordingly, embodiments herein contemplate that the EN 14 may be configured to, as an alternative to the estimation(s) provided in accordance with Equations (1)-(3), otherwise determine which of the plurality of RPs 17 is nearest in proximity to the EN 14 by evaluating a coordinate location of each of respective ones of the plurality alongside an evaluation of their RSSs. This way, the alternative estimation performed by the EN 14 enhances the outcome determined in accordance with Equations (1)-(3) by supplementing it with relative positioning for a given RP 17.

Thus, in referring to FIG. 7, there is illustrated an exemplary setting 30, such as may be implemented on a floor of a building whereby an EN 14 is confronted with determining a nearest proximity RP 17 from among a plurality of RPs 17 each of which is separated by an artificial boundary such as a wall. Determining of the nearest proximity is contemplated to reduce distortions in location estimation due to interference caused by such a boundary, or other interference, as the EN 14 moves throughout the floor.

Generally, and for ease of discussion, setting 30 corresponds to a predetermined floor plan having a number of zones (Z) each containing an RP 17 (though more than one RP 17 may be contained within any one zone). Upon activation, RP 17 will initially function as an EN 14 so as to receive, via communication with network 22 through AP 16, its initial provisioning to function as an RP 17. Such provisioning will also include assigning, based on the network's own mapping of RPs 17 within the setting 30, a set of coordinates to the RP 17 to identify the exact location of the fixed location of the RP 17 within the setting 30. As will be understood, the setting 30 may be of any configuration, as will the nature of the coordinates that comport therewith. In the interest of brevity and for purposes of explanation herein, such coordinates of any one RP 17 may be assigned as Cartesian coordinates according to x-y axes made applicable upon setting 30.

With continuing reference to FIG. 7, setting 30 may be divided into an exemplary number of zones Z₁ through Z₈ (, each having a corresponding, respective Zone ID), though other types of configurations and divisions are contemplated. Although shown as containing a single RP 17 in each zone, it will be understood that multiple RPs 17 may be stationed within a zone in accordance with the particularized layout of setting 30. This way, EN 14 may detect respective beacon advertisements which are broadcast from the one or more RPs 17 so as to estimate a nearest proximity thereto.

As has been discussed, each RP 17 will be associated with its own (x,y) coordinate and zone description according to setting 30 as defined by network 22. In other words, network 22 retains a mapping of each of the RPs 17 according to their (x,y) coordinate and zonal locations, and is enabled to communicate such information to one or more APs 16 operating in and/or relative to the setting 30. For instance, each AP 16 operating within setting 30 may be preloaded, i.e., provisioned by network 22, with RP 17 coordinate and zonal location information.

As EN 14 moves throughout setting 30, it is contemplated that it obtain position information, and specifically the (x,y) coordinate information, of a detected one or more RPs 17, according to one of at least two collection methods. First, the EN 14 may collect the (x,y) coordinate information of any RP 17 as data that is included in any RP advertisement received by the EN 14. Second, each RP 17 may be configured to broadcast, as part of its advertisement, area information indicating that it belongs to, for instance, a particular area or zone, e.g., one of Z₁ through Z₈, as exemplary of the area information within setting 30, which, as discussed above, may be of any configuration such that the area information may be described other than by zones. Having receiving the advertisement, the EN 14 may then query the AP 16 for information regarding RPs for the received area or zone, and receive from an AP 16 to which it has connected (according to Equation 4) the (x,y) coordinate information and corresponding RP association for all RPs 17 located within the received area or zone. Notably, the coordinate information regarding the associated RP, as transmitted by the AP 16, further defines a graph of portions of the setting 30 in which there exists an opportunity for allowable path and transitions. Such a graph is particularly applicable in the instance in which the setting 30 is embodied as a floorplan comprising various arrangements of doorways and hallways, for instance. In this example, the graph is contemplated to represent the floor plan according to, at least, nodes and edges indicating the doorways and hallways, respectively. The query by the EN 14 may be made recursively of the same or a different AP 16 with respect to zones that the EN 14 may successively encounter. The result is that the EN 14 accumulates a mapping of the RPs 17 according to their (x,y) coordinates, whether obtained solely from RP advertisements or from fulfillment of the request(s) by one or more APs 16.

In view of the above, an EN 14 is equipped to estimate the nearest RP 17 within setting 30 based on, with respect to a given one or more RPs 17, both (a) RSS and (b) coordinate information. As such, the estimate conducted by the EN 14 is supplemented by the coordinate information, in contrast to the RSS evaluation discussed above in connection with Equations (1)-(3). Thus, it will be understood that this supplementation represents an alternative EN location estimate relative to the estimate otherwise achieved solely in accordance with Equations (1)-(3).

Calculation by the EN 14 of this alternative estimate may be carried out according to several techniques. They include performing, for a plurality of advertisements received from an RP 17, (A) a determination of a weighted average of coordinate information and RSS to achieve a coordinate estimate of the EN 14 to the RP 17, (B) a determination in accordance with trilateration, and (C) a determination in accordance with simplified trilateration. Each of these techniques is discussed in greater detail below.

(A) Weighted Average of RP Coordinate Information and RSS

Since an EN 14 has at its disposal both coordinate information and RSS for a given RP 17 which it has detected, it makes sense to determine an actual estimate of a coordinate location of the EN 14 within exemplary setting 30. Such an actual estimate of the EN's location is obtainable based on the received coordinates for all the RPs 17 whose advertisements have been received by the EN 14. Once obtained, the actual estimate is compared to each of the received RP coordinates. Based upon this comparison, the EN 14 can then report its location to the best AP 16 connection in terms of the MAC address of the RP 17 whose coordinates are nearest, i.e., most closely match, the actual coordinate estimate determined by and for the EN 14 itself.

Calculation of the estimated EN 14 coordinate is performed individually (and identically) for each x and y component thereof. For instance, the x component is determined with respect to the x coordinate component for a given RP 17, as provided below in Equation (5).

$\begin{matrix} {{x = {\sum\limits_{i = 1}^{N}{a_{i}x_{{RP},i}}}},} & {{Equation}\mspace{14mu} (5)} \end{matrix}$

in which N represents the number of reference points, X_(RP,i) represents the x component of the RP's coordinate location, and a_(i) represents a weighting factor assigned to each observation based on the RSS for the given reference point as detected by the EN 14. The weights, a_(i), are calculated as provided in Equation (6), wherein

${a_{{RP},i} = \frac{r_{i} - r_{\min}}{{\sum\limits_{i = 1}^{N}r_{i}} - r_{\min}}},$

in which r_(i) represents the RSS for a given RP as detected by the EN 14, r_(min) is the sensitivity (in dBm) of the receiver. Throughout, the weights, a_(i), sum to one, as per Equation (7), wherein

Σ_(i=1) ^(N) a _(RP,i)=1.

(B) Trilateration

In this technique, an EN 14 will employ a path loss model (such as a free space path loss (FSPL) model) to estimate its location in terms of which RP 17 is most proximate. The resultant path loss is assessed for each RP 17 relative to a an appropriate likelihood function, whereby maximization thereof represents the greatest proximity to the EN 14.

More specifically, the path loss (in dBm) may be expressed as follows, per Equation (8), wherein

${P_{L} = {\frac{P_{t}}{P_{r}} = \left( \frac{4\pi \; d}{\lambda} \right)^{2}}},$

in which P_(t) and P_(r) represent the transmit and receive powers of an RP 17 and EN 14, respectively, d (in meters) is the distance between the transmitter and receiver thereof, respectively, and A (in meters) is the wavelength of the radio emission. Multiplicative effects on the transmission channel, such as body occlusion and structural loss, are combined with occurrences of additive noise.

FIG. 7A provides a diagrammatic representation of the estimated location of the EN 14 according to the trilateration technique, whereby the location of an EN 14 relative to the transmitting ENs is indicated by the shown intersection therein.

In FIG. 7A, the distance, d_(i) is a Euclidean distance relative to the location vector state, e.g., x-y coordinates, of a given RP_(i), or L_(i), and the location vector state of the EN 14, θ (as determined continually upon receipt of beacon advertisement messages and expressed in terms of x-y coordinates as measurements of proximity to the transmitter(s)), and is given by Equation (9), wherein

d _(i) =∥θ−L _(i)∥₂.

When rearranged to provide for a respective EN 14 receive power, P_(r,i) (in dBm), and while substituting Equation (9), Equation (5) may be rewritten as Equation (10), wherein

$P_{r,i} = {P_{t,i} + {20\mspace{14mu} {\log_{10}\left( \frac{\lambda}{4\pi} \right)}} - {20\mspace{11mu} \log_{10}{{{\theta - L_{i}}}_{2}.}}}$

Further simplification of Equation 10, such that P_(t,i) and

$20\mspace{14mu} {\log_{10}\left( \frac{\lambda}{4\pi} \right)}$

are known, provides consolidation of these known parameters into a constant, a, as shown by Equation (11), in which

$a = {P_{t,i} + {20\mspace{14mu} {{\log_{10}\left( \frac{\lambda}{4\pi} \right)}.}}}$

Thus, Equation (10) may be rewritten as Equation (12) and to further include additive noise N, wherein

P _(r,i) =a−20 log₁₀ ∥θ−L _(i)∥₂ +N.

As such, it will be understood that the observable received power of a transmitting EN 14 is a function of an unobservable vector state, θ, of an EN 14. Therefore, for a given observation, the likelihood function may be expressed as Equation (13), wherein

${p_{R|\theta}\left( {\left. r_{i} \middle| \theta \right.,P_{r,i}} \right)} = {\frac{1}{\sqrt{2\pi \; \sigma_{PL}^{2}}}{e^{- \frac{{({r_{i} - p_{r,i}})}^{2}}{2\sigma_{PL}^{2}}}.}}$

Further, and in assuming that each observation should be considered conditionally independent of another, Equation (13) may be rewritten as Equation 14, in which

${p_{R|\theta}\left( {\left. r_{N} \middle| \theta \right.,P_{r,1},P_{r,2},\ldots \;,P_{r,N}} \right)} = {\prod\limits_{i = 1}^{N}\; {{p_{R|\theta}\left( {\left. r_{i} \middle| \theta \right.,P_{r,i}} \right)}.}}$

Accordingly, relative to the diagrammatic illustration in FIG. 7A representing a location of the EN 14 as the intersection between triangulated locations from the shown transmitters, a location estimate, {circumflex over (θ)}_(ML), representing a value of θ that maximizes Equation (14), is given by Equation (15), in which

${\hat{\theta}}_{ML} = {\begin{matrix} {argmax} \\ \theta \end{matrix}{\prod\limits_{i = 1}^{N}\; {p_{R|\theta}\left( {\left. r_{i} \middle| \theta \right.,P_{r,i}} \right)}}}$

and may be reduced to either Equation (16) or (17), as shown respectively below.

$\begin{matrix} {{\hat{\theta}}_{ML} = {\begin{matrix} {argmax} \\ \theta \end{matrix}{\sum\limits_{i = 1}^{N}{\ln \; {p_{R|\theta}\left( {\left. r_{i} \middle| \theta \right.,P_{r,i}} \right)}}}}} & {{Equation}\mspace{14mu} (16)} \\ {{\hat{\theta}}_{ML} = {{\begin{matrix} {argmax} \\ \theta \end{matrix}C\; 1} + {\frac{1}{2\sigma_{PL}^{2}}{\sum\limits_{i = 1}^{N}\left( {r_{i} - P_{r,i}} \right)^{2}}}}} & {{Equation}\mspace{14mu} (17)} \end{matrix}$

Based on the above, the maximum likelihood estimate, {circumflex over (θ)}_(ML), indicating the triangulated position of an EN 14 may be expressed according to Equation (18), in which

${{\hat{\theta}}_{ML} = {{\begin{matrix} {argmax} \\ \theta \end{matrix}C\; 1} + {\frac{1}{2\sigma_{PL}^{2}}{\sum\limits_{i = 1}^{N}\left( {r_{i} - P_{r,i}} \right)^{2}}}}},$

which may be further reduced and expressed (through the exclusion of inapplicable parameters) as the following Equation (19) providing

${\hat{\theta}}_{ML} = {\begin{matrix} {argmax} \\ \theta \end{matrix}{\sum\limits_{i = 1}^{N}{\left( {r_{i} - P_{r,i}} \right)^{2}.}}}$

In the above respects, the determined nearest proximity to a RP 17 is evaluated via the above-discussed trilateration in connection with RSS for a plurality of RPs encountered by the EN 14. In these ways, the coordinates provided to an RP 17 may be more acutely interrogated in light of corresponding RSS to narrow an estimation of proximity of the EN 14.

(C) Simplified Trilateration

In an effort to smoothen the resultant likelihood(s) yielded by Equation (14), such implementation of that equation and likelihood(s) rendered thereby may be considered to be a multidimensional Gaussian. In doing so, an evolving multidimensional covariance of a combined Gaussian likelihood is disregarded, such that there is yielded a combined likelihood function having symmetric geometry in the x and y directions, i.e., σ_(x) ²=σ_(y) ², with correlation coefficients ρ_(xy)=ρ_(yk)=0. Accordingly, the standardized two dimensional covariance, relative to a combination of at least a pair of likelihood functions, of

$\Sigma = \begin{bmatrix} \sigma_{x}^{2} & {\rho_{xy}\sigma_{x}\sigma_{y}} \\ {\rho_{yx}\sigma_{x}\sigma_{y}} & \sigma_{y}^{2} \end{bmatrix}$

is reduced to

$\Sigma = {\begin{bmatrix} \sigma_{PL}^{2} & 0 \\ 0 & \sigma_{PL}^{2} \end{bmatrix}.}$

Based on the above, combinations of multidimensional likelihoods, as may be yielded by Equation (14), are simplified to provide series of one dimensional likelihood combinations that are projected onto the dimension between the pair of likelihoods under consideration. Additionally, as a result of the above simplification(s), the maximum likelihood estimate, {circumflex over (θ)}_(ML), may be replaced as the mean of the determined Gaussian likelihood.

Further, it is contemplated that, once having accumulated aggregate coordinate information for setting 30, the EN 14 may employ Equations (1)-(3) to further refine any estimated EN location determined in accordance with techniques (A)-(C). Doing so allows the EN 14 to employ the accumulated knowledge of the setting 30 in order to reactively hone its proximity determination to a given RP 17 when further RP advertisements are received.

Operation of the EN 14 in accordance with the above-described alternative manner of EN location determination with respect to a RP 17 is depicted in FIG. 8. Therein, the operation starts at decision block 810 whereat an EN 14 will identify, in accordance with Equation (4), the best AP connection within, for example, the discussed setting 30. Flow proceeds to block 820 in which the EN 14 will receive, as part of a RP's advertisement, either (a) all of the (x,y) coordinates or (b) the Zone ID, for those RPs 17 which are detectable. At block 830, in response to the EN querying the connected AP 16 for the (x,y) coordinates for RPs within any Zone ID which it has received, the EN 14 receives a mapping of such coordinates to their respective RPs within the identified zone. At this stage, it is likely that, since multiple RP advertisement may mix transmission of (x,y) coordinates alone with identifications of Zone IDs, the EN 14 has accumulated its own RP 17 mapping of those portions of setting 30 which it has traversed. Accordingly, based upon this mapping, the EN 14 is equipped, at decision block 840, to estimate its own coordinates according to its collected RP 17 (x,y) coordinates and their corresponding RSS. At block 850, once the estimate is complete, the EN 14 may then transmit to the connected AP 16 its estimated location (in terms of the particular RP 17 to which it is most proximate according to the estimate of its own EN location). The determination as to which RP 17 is most proximate the EN 14 is made based on the EN 14 conducting a comparison of its own estimated location to the (x,y) coordinates for all those RPs 17 for which it has detected a beacon advertisement message. As a result, the transmitted location will comprise messaging detailing the MAC address of the particular RP 17 that has been determined as being nearest in proximity to the EN 14. The AP 16 will then, at block 860, transmit such MAC address to network 22 for receipt and analysis thereby to verify the EN's estimated location relative to knowledge of the setting 30, and perhaps, prior location estimates reported by the EN 14 in combination with timing of those reports. In other words, network 22 may conduct its own analysis to ensure that the estimated location comports with a predetermined time and distance threshold so as to discard location estimates that may exceed such threshold.

In these ways, it will be understood that the embodiments disclosed herein optimize the efficiency of a BLE-enabled network by, at least, reducing burdens on network resources, as well as by enhancing the likelihood of connection in situations in which multiple end nodes are co-located. It will likewise be understood that the embodiments disclosed herein enable a determination of the relative location of an end node in view of its proximity to an access point, and one or more reference points.

It will be understood that each of the APs 16 and RPs 17 described herein may be configured to include directional and circularly polarized antennas to, respectively, better focus their broadcasts and reduce cross polarization loss sometimes experienced with vertically polarized antennas. This way, EN 14 proximity determinations may be achieved with increased accuracy.

The present embodiments are not limited to the particular embodiments illustrated in the drawings and described above in detail. Those skilled in the art will recognize that other arrangements could be devised. The present embodiments encompass every possible combination of the various features of each embodiment disclosed. One or more of the elements described herein with respect to various embodiments can be implemented in a more separated or integrated manner than explicitly described, or even removed or rendered as inoperable in certain cases, as is useful in accordance with a particular application While the present embodiments have been described with reference to specific illustrative embodiments, modifications and variations of the present embodiments may be constructed without departing from the spirit and scope of the present embodiments as set forth in the following claims.

While the present embodiments have been described in the context of the embodiments explicitly discussed herein, those skilled in the art will appreciate that the present embodiments are capable of being implemented and distributed in the form of a computer-usable medium (in a variety of forms) containing computer-executable instructions, and that the present embodiments apply equally regardless of the particular type of computer-usable medium which is used to carry out the distribution. An exemplary computer-usable medium is coupled to a computer such the computer can read information including the computer-executable instructions therefrom, and (optionally) write information thereto. Alternatively, the computer-usable medium may be integral to the computer. When the computer-executable instructions are loaded into and executed by the computer, the computer becomes an apparatus for practicing the embodiments. For example, when the computer-executable instructions are loaded into and executed by a general-purpose computer, the general-purpose computer becomes configured thereby into a special-purpose computer. Examples of suitable computer-usable media include: volatile memory such as random access memory (RAM); nonvolatile, hard-coded or programmable-type media such as read only memories (ROMs) or erasable, electrically programmable read only memories (EEPROMs); recordable-type and/or re-recordable media such as floppy disks, hard disk drives, compact discs (CDs), digital versatile discs (DVDs), etc.; and transmission-type media, e.g., digital and/or analog communications links such as those based on electrical-current conductors, light conductors and/or electromagnetic radiation.

Although the present embodiments have been described in detail, those skilled in the art will understand that various changes, substitutions, variations, enhancements, nuances, gradations, lesser forms, alterations, revisions, improvements and knock-offs of the embodiments disclosed herein may be made without departing from the spirit and scope of the embodiments in their broadest form. 

What is claimed is:
 1. A BLE communications system, comprising: an end node (EN); an access point (AP) configured to connect to a network and transmit a first beacon advertisement message; and a plurality of reference points (RPs) each configured to not connect to the network and transmit a second beacon advertisement message comprising position information, in which the EN is configured to detect the first and second beacon advertisement messages, initiate a connection with the AP in which, as a result of the connection, the AP is caused to transfer to the network identifying information of each of the EN and the AP, and determine, as against others of the plurality of RPs, whether a proximity of a respective one of the plurality of RPs to the EN is a nearest proximity based on the position information and a received signal strength (RSS) of each of the detected second beacon advertisement messages, and wherein the EN determines whether to initiate the connection with the AP in response to evaluating from the detected first beacon advertisement message at the time of transmission of the first beacon advertisement message each of at least (a) whether a proximity of the AP to the EN is a nearest proximity and (b) a loading of the network to which the AP is connected, and transmits, via the connection, identifying information of the respective one of the plurality of RPs to the network in response to a determination that the respective one of the plurality of RPs is nearest in proximity to the EN, from among others of the plurality.
 2. The BLE communications system of claim 1, wherein: the position information comprises coordinate information or area information for an area, among contiguous areas, of a predetermined setting containing one or more of the plurality of RPs.
 3. The BLE communications system of claim 2, wherein: one or more of the plurality of RPs is configured to include the area information in the second beacon advertisement message thereof, the EN is configured to query the AP for the coordinate information corresponding to the area information, and the AP is configured to fulfill the query so as to supply the corresponding coordinate information to the querying EN.
 4. The BLE communications system of claim 3, wherein: the coordinate information comprises, relative to an x-y coordinate system, an x component and a y component.
 5. The BLE communications system of claim 4, wherein: the EN is further configured to determine the respective one RP as being nearest in proximity to the EN by comparing an estimated coordinate position of the EN as against each of the coordinates corresponding to the RPs.
 6. The BLE communications system of claim 5, wherein: the estimated coordinate position is determined according to, for each RP, a calculation of a weighted average of the RP coordinate information and the RSSs received therefrom.
 7. The BLE communications system of claim 6, wherein: the weighted average is calculated separately for each coordinate component.
 8. The BLE communications system of claim 7, wherein: the calculation of the weighted average for each of the x and y components yields the estimated coordinate position of the EN within the x-y axis system, relative to each RP.
 9. The BLE communications system of claim 8, wherein: the EN is further configured to update the determination of the respective nearest proximity RP in accordance with a Bayesian maximum a posteriori (MAP) estimation for each of the RSSs corresponding to the plurality of detected second beacon advertisement messages.
 10. The BLE communications system of claim 2, wherein: the EN is further configured to determine the respective one RP as being nearest in proximity to the EN based on path loss and trilateration relative thereto, with respect to the RSSs corresponding to the second beacon advertisement messages.
 11. The BLE communication system of claim 10, wherein: the likelihood rendered according to the trilateration is a multidimensional Gaussian.
 12. The BLE communications system of claim 10, wherein: the EN is further configured to update the determination of the respective nearest proximity RP in accordance with a Bayesian maximum a posteriori (MAP) estimation for each of the RSSs corresponding to the plurality of detected second beacon advertisement messages.
 13. A method of BLE communication, comprising: executing, by one or more processors among a BLE end node (EN), a BLE access point (AP) configured to connect to a network, and a plurality of BLE reference points (RPs) configured to not connect to the network, a set of instructions for transmitting a first and a second beacon advertisement message from the AP and each of the plurality of RPs, respectively, each second beacon advertisement message comprising position information, detecting the first and the second beacon advertisement messages at the EN, initiating a connection between the AP and the EN, in which, as a result of the connection, the AP is caused to transfer to the network identifying information of each of the EN and the AP, and determining, as against others of the plurality of RPs, whether a proximity of a respective one of the plurality of RPs is a nearest proximity based on the position information and received signal strengths (RSSs) of the second beacon advertisement messages, wherein the EN determines whether to initiate the connection with the AP in response to evaluating from the detected first beacon advertisement message at the time of transmission of the first beacon advertisement message each of at least (a) whether a proximity of the AP to the EN is a nearest proximity and (b) a loading of the network to which the AP is connected, and transmits, via the connection, identifying information of the respective one of the plurality of RPs to the network in response to a determination that the respective one of the plurality of RPs is nearest in proximity to the EN, from among others of the plurality.
 14. The method of BLE communication of claim 13, wherein: the position information comprises coordinate information or area information for an area, among contiguous areas, of a predetermined setting containing one or more of the plurality of RPs.
 15. The method of BLE communication of claim 14, wherein: one or more of the plurality of RPs is configured to include the area information in the second beacon advertisement message thereof, the EN is configured to query the AP for the coordinate information corresponding to the area information, and the AP is configured to fulfill the query so as to supply the corresponding coordinate information to the querying EN.
 16. The method of BLE communication of claim 15, wherein: the coordinate information comprises, relative to an x-y coordinate system, an x component and a y component.
 17. The method of BLE communication of claim 16, wherein: the EN is further configured to determine the respective one RP as being nearest in proximity to the EN by comparing an estimated coordinate position of the EN as against each of the coordinates corresponding to the RPs.
 18. The method of BLE communication of claim 17, wherein: the estimated coordinate position is determined according to, for each RP, a calculation of a weighted average of the RP coordinate information and the RSSs received therefrom.
 19. The method of BLE communication of claim 18, wherein: the weighted average is calculated separately for each coordinate component.
 20. The method of BLE communication of claim 19, wherein: the calculation of the weighted average for each of the x and y components yields the estimated coordinate position of the EN within the x-y axis system, relative to each RP.
 21. The method of BLE communication of claim 20, wherein: the EN is further configured to update the determination of the respective nearest proximity RP in accordance with a Bayesian maximum a posteriori (MAP) estimation for each of the RSSs corresponding to the plurality of detected second beacon advertisement messages.
 22. The method of BLE communication of claim 14, wherein: the EN is further configured to determine the respective one RP as being nearest in proximity to the EN based on path loss and trilateration relative thereto, with respect to the RSSs corresponding to the second beacon advertisement messages.
 23. The method of BLE communication of claim 22, wherein: the likelihood rendered according to the trilateration is a multidimensional Gaussian.
 24. The method of BLE communication of claim 22, wherein: the EN is further configured to update the determination of the respective nearest proximity RP in accordance with a Bayesian maximum a posteriori (MAP) estimation for each of the RSSs corresponding to the plurality of detected second beacon advertisement messages. 